Calciomics is a specialized area of biochemistry focusing on the study of calcium-binding biological macromolecules and proteins to understand the factors that contribute to calcium-binding affinity and the selectivity of proteins and calcium-dependent conformational change.
The objective of this research is to develop bioinformatics methods to predict and identify different classes of calcium binding sites in proteins. In collaboration with Dr. GT Chen in the Georgia State University Department of Mathematics and Statistics, algorithms for predicting calcium binding sites based on structural and genomic information have been established using geometric, graphing, and statistical algorithms along with a web sever containing up-to-date sequence, structure and literature information about calcium and its binding proteins in chemical, biological, and biomineralization. The Calcium Bank also provides putative calcium binding sites predicted in different genomes.
CaPS (Calcium Pattern Search) provides a list of Ca(II)-binding AA sequence patterns that indicate the presence of a Ca(II)-binding motif. To date, we have developed sequence patterns, or signatures, for canonical EF-hand, pseudo EF-hand, and baterial EF-hand. We expect to significantly expand this list in the future to indlude non-contiguous (binding motif includes AA residues distant from each other in the primary structure) patterns. To check a sequence for the presence of a Ca(II)-binding signature click on the CaPS link and enter your sequence for analysis.
GG is a graph-theoretic and geometric analysis program developed by Hai Deng, Guan Tao Chen, Wei Yang, and Jenny J Yang. The program is used for predicting Ca(II)-binding sites in protein based on the geometric information.
MUG is a prediction algorithm with atomic resolution of calcium-binding sites in proteins. After first identifying all possible oxygen clusters by finding maximal cliques, a calcium center (CC) for each cluster, corresponding to the potential Ca2+ position, is located to maximally regularize the structure of the (cluster, CC) pair. The structure is then inspected by geometric filters. An unqualified (cluster, CC) pair is further handled by recursively removing oxygen atoms and relocating the CC until its structure is either qualified or contains fewer than four ligand atoms. Ligand coordination is then determined for qualified structures.
<Beta Version >MUGC recognizes Ca(2+)-binding sites without explicit reference to side-chain oxygen ligand coordinates. By using second shell carbon atoms, main-chain oxygen atoms, center of mass of side-chain, and graph theory, it is able to predict calcium-binding sites exibiting insignificant conformational change with high sensitivity and selectivity based on X-ray structures or NMR structures.
Our publications in regard to calciomics are shown below:
Kun Zhao, Xue Wang, Michael Kirberger, Hing Wong, Guantao Chen, and Jenny J. Yang, Predicting Calcium-binding Site Using Second Shell Carbon Atoms, Submitted.
Xue Wang, Michael Kirberger, Guantao Chen, and Jenny J. Yang, Towards Predicting Ca(2+)–binding Sites with Different Coordination Numbers in Proteins with Atomic Resolution. Proteins (2009), 75, 1099-1107.
Yubin Zhou, Wei Yang, Michael Kirberger, Hsiau-Wei Lee, Gayatri Ayalasomayajula, and Jenny J. Yang. Prediction of EF-hand Calcium Binding Proteins and Analysis of Bacterial EF-hand Proteins. Proteins (2006), supplementary.
Hai Deng, Guantao Chen, Wei Yang, Jenny J. Yang. Predicting calcium-binding sites in proteins - a graph theory and geometry approach. Proteins (2006), 64, 34-42.
Wei Yang, Hsiau-wei Lee, Homme Hellinga and Jenny J. Yang. Identification and Design of Metal-Binding Proteins. Proteins (2002), 47 , 344-356.
Wei Yang, Hsiauwei Lee, Homme Hellinga , Michelle Pu and Jenny Jie Yang. Design Calcium Binding Sites by Computer Algorithm. Computational Studies, Nanotechnology , and Solution Thermodynamics of Polymer Systems . Kluwer Academic/Plenum Publishers (2000) ,127-138.